Dynamics of iron metabolism in patients with bloodstream infections: a time-course clinical study

The close relationship between infectious diseases and iron metabolism is well known, but a more detailed understanding based on current knowledge may provide new insights into the diagnosis and treatment of infectious diseases, considering the growing threat of antibiotic-resistant bacteria. This study investigated adult patients with bloodstream infections, temporal changes, and relationships between blood levels of iron and related markers, including hepcidin and lipocalin-2 (LCN2). We included 144 samples from 48 patients (mean age 72 years, 50% male), with 30 diagnosed with sepsis. During the acute phase of infection, blood levels of hepcidin and LCN2 increased rapidly, whereas iron levels decreased, with values in 95.8% of cases below the normal range (40–188 μg/dL). Later, hepcidin and LCN2 decreased significantly during the recovery phase, and the decreased iron concentrations were restored. In the case of persistent inflammation, iron remained decreased. Acute LCN2 levels were significantly higher in patients with sepsis (p < 0.01). Hypoferremia induced by increased hepcidin would reduce iron in the environment of extracellular pathogens, and the increased LCN2 would inhibit siderophores, resulting in the prevention of the pathogen’s iron acquisition in each manner during the acute phase of bloodstream infection.

While factors involved in iron metabolism are becoming increasingly clear, the relationship between iron metabolism and infection is often presented in the context of chronic inflammation and anemia 16,17 .In addition, the current understanding of the relationship between iron metabolism and infection, particularly in acute infection models, is primarily derived from animal studies 18 .Thus, there remains scope for further exploration in understanding iron metabolism in the realm of human infectious diseases.In addition, in the modern context of the emergence of drug-resistant bacteria, a new approach to the pathophysiology of infectious diseases is urgently needed, and iron metabolism is considered a particularly attractive target.Against this background, this research aims to further investigate infectious diseases through the axis of iron metabolism, focusing on hepcidin and LCN2.To this end, we have comprehensively analyzed iron metabolism and inflammatory markers during bloodstream infection using clinical samples.

Iron kinetics and associated markers
During the clinical course of the bloodstream infections, the temporal changes of the iron metabolism and inflammation markers are shown in Fig. 1.In the context of this study, the values measured at D10 were considered the baseline against which the values measured at D1 and D3 were compared.Blood levels of inflammatory markers such as interleukin 6 (IL-6) and C-reactive protein (CRP), as well as white blood cell (WBC) count, rose during the infection's acute period (D1 and D3).Additionally, blood levels of iron-related hepcidin and LCN2 also increased when compared to D10.In contrast, iron levels decreased, with 95.8% of cases having iron levels below the normal range (40-188 μg/dL) at D1 or D3.In the recovery phase (D10), as the immune system and treatment brought the infection under control, WBC and levels of IL-6, CRP, hepcidin, and LCN2 substantially decreased compared to the acute phase of infection.Iron levels showed a recovery trend and increased to within the reference range in 62.5% of cases.During the study, the median change in iron concentration was 31 μg/dL (maximum 104 μg/dL, IQR 21-63 μg/dL).Table 2 presents representative values for all measured parameters at each point.Another marker related to iron metabolism is ferritin, increased during the acute phase and then decreased like other acute-phase proteins.In contrast, unsaturated iron-binding capacity (UIBC) and total ironbinding capacity (TIBC), like iron, decreased during the acute phase of infection.TIBC increased significantly during the recovery phase, whereas UIBC did not.Furthermore, a line graph (Fig. S1) shows case-specific iron and inflammatory markers trends in the 19 hospital-onset cases.The community-onset cases were excluded to make the time from onset to positive blood culture (D1) as uniform as possible.Measurements at each point were compared as related pairs.As a result, a typical variation pattern appeared for each parameter, consistent with the result described above.Among them, CRP and LCN2 were the highest at D3 in most cases (89.5% and 78.9%, respectively), and iron was the lowest at D3 in 89.5% of cases.Hepcidin, on the other hand, was the highest at D1 in most cases (68.4%), indicating earlier hepcidin elevation during the acute phase.www.nature.com/scientificreports/presepsin (ρ = − 0.45) and hepcidin (ρ = − 0.40).On the other hand, the iron concentration showed a weak positive correlation with albumin and TIBC (both ρ = 0.39).Hepcidin showed a moderate positive correlation with CRP (ρ = 0.60), IL-6 (ρ = 0.60), and ferritin (ρ = 0.52).LCN2 showed a moderate positive correlation with CRP (ρ = 0.59), neutrophils (ρ = 0.59), IL-6 (ρ = 0.58), and WBC (ρ = 0.51).Table S3 shows the correlation coefficients between all measured parameters (17 items).Principal component analysis (PCA) was performed on all samples measured from D1 to D10.Table S4 displays the eigenvectors of principal components 1 (PC1) to 4 (PC4).The first two PCs accounted for 41.6% of the variation in the data set.For PC1, variables related to infection and inflammation such as WBC, neutrophils, and presepsin predominated with high positive eigenvector values.For PC2, albumin and transferrin (represented by TIBC) predominated with large positive eigenvector values.Score plots revealed the data distribution without outliers (Fig. 4A).While D1 and D3 samples appeared to have similar clustering patterns, D10 samples revealed a distinct distribution.This shift from D1 and D3 to D10 indicates dynamic changes in the influence of the parameters over time.In the loading plot (Fig. 4B), both hepcidin and LCN2 were found to cluster with WBC, neutrophils, presepsin, and CRP.Conversely, iron clustered in the opposite quadrant to these parameters, suggesting a negative correlation.

Discussion
Our study comprehensively evaluated host iron metabolism in bloodstream infections using clinical blood samples.We detailed the temporal dynamics of several parameters related to iron metabolism and inflammatory markers, focusing on the dynamics of hepcidin, the master regulator of iron.A rapid increase in the acute phase typically characterized the time course of blood hepcidin levels.This outcome was consistent with a prior experiment using an lipopolysaccharide (LPS) injection 20 and a typhoid infection 21 on a human volunteer.In contrast to hepcidin, iron levels decreased rapidly, although the iron levels tended to decrease later than the increase in hepcidin levels during the acute phase.Because the present study targeted bloodstream infections, the effect of hepcidin may contribute to the host's innate immunity by reducing the amount of iron in the extracellular pathogen's environment, thereby inhibiting iron acquisition.This observation is consistent with previous findings 2, 3,18 .
In contrast, iron is an essential nutrient for host homeostasis, and persistent iron deficiency in the blood should be avoided 2 .In this study, hypoferremia in the acute phase was transient.As the infection was controlled and resolved, there was a progressive decrease in hepcidin levels and a corresponding increase in iron levels.If inflammation persisted, iron levels remained low for a prolonged period.Our time course analysis provides a clearer and more comprehensive understanding of how the human body manages and regulates iron during these critical periods.
The current study also includes blood levels of another iron-related factor, LCN2.It is engaged in several physiological and pathophysiological processes, such as inflammation, infection, immune response, and metabolic homeostasis 22 .The present results show that blood levels of LCN2 increase during the acute phase of systemic infection and decrease during the recovery phase, consistent with a previous report using a mouse model 23 .Furthermore, LCN2 levels were significantly elevated during the acute phase of sepsis and showed a significant www.nature.com/scientificreports/correlation with the D1 SOFA score, indicating its potential as a marker of sepsis severity.The LCN2 knockout mice also showed a protective role in sepsis, as organ damage and mortality were worse in LCN2 knockout mice than in wild-type mice after LPS injection 23 .Therefore, the present results suggest an important action of LCN2 in sepsis pathogenesis, warranting further study.LCN2 is considered an effective biomarker of acute kidney injury 24 .In addition to a strong inflammatory response, LCN2 levels may have been affected by the kidney injury associated with bloodstream infection, including sepsis, in the present study.However, no correlation was found between creatinine and LCN2 levels, and the effect was considered limited in the study.The present study reiterated the close relationship between inflammation and iron metabolism in acute systemic infections.A possible starting point for these findings is the involvement of the inflammatory cytokine IL-6, released by immune cells in response to infection or injury.In a previous report, plasma iron and TIBC levels decreased and then recovered after IL-6 administration in animal models 25 .In general, blood levels of IL-6 increase rapidly during the early stages of infection, from hours to days 27 .Acute-phase proteins like CRP, ferritin, hepcidin, and LCN2 are induced by IL-6 3,4,15,26 .On the other hand, IL-6 decreases albumin and transferrin production 27 .These effects of IL-6 were consistent with the results of the current study, including time trends of each measure, correlations, and PCA.
In recent years, the spread of multidrug-resistant bacteria has become a global problem, and the development of antibiotics with new mechanisms of action is urgently needed.In this setting, the bacterial iron transport  12) groups.WBC (a), IL-6 (b), CRP (c), iron (d), HEP (e), and LCN2 (f) blood levels at D1 were measured and compared between two groups.In box-and-whisker plots, the thick line represents the median, and the boxes represent the interquartile range.The median of each point is connected by a solid line.A logarithmic scale is used for the IL-6 Y-axis.Measurements were compared between points, and P-values were calculated using the Wilcoxon signed-rank test.Statistically significant items are marked with an asterisk (*).WBC white blood cell count, IL-6 interleukin-6, CRP C-reactive protein, HEP hepcidin, LCN2 lipocalin-2.
Vol:.( 1234567890 www.nature.com/scientificreports/mechanism is an attractive site of action for antimicrobial agents.Siderophore cephalosporins can efficiently penetrate the outer membrane through the bacterial iron transport system by forming iron chelate complexes 28 and are reportedly effective against multidrug-resistant Gram-negative bacteria [29][30][31] .Therefore, the dynamics of iron metabolism in the clinical course of this study are expected to be useful for the effective use of such antimicrobial agents.Under iron-deficient conditions, bacteria upregulate the siderophore and the iron transporter system 32,33 .Data are expressed as median (interquartile range) or mean ± standard error.Asterisks denote significant differences (p < 0.05).P-values near the significance boundary are represented with three decimal places for precision.a Persistent inflammation is defined in this study following the criteria outlined in Nakamura et al. 19 .

Persistent inflammation a p value (n = 37)
(n = 11) www.nature.com/scientificreports/Consistent with this finding, in vitro studies have shown that the concentration of iron in the culture medium affects the antimicrobial activity of siderophore cephalosporins, with lower minimum inhibitory concentrations in iron-deficient situations 28 .Therefore, the hypoferremia shown in this study during the acute phase of systemic infections may also enhance the efficacy of such antimicrobial agents in vivo.
There are several limitations to this research.First, it was a single-center study conducted at a university hospital and included a relatively small number of patients with diverse clinical backgrounds, and the possibility of unintentional selection bias cannot be excluded.Second, it was not possible to establish baseline values for each parameter before disease onset.It was difficult to determine the onset of bloodstream infections in advance, so the values measured during the recovery phase, D10, were used for comparison.Third, because there were no deaths in this study, we could not examine the relationship between poor prognoses and iron metabolism in bloodstream infections.To address this issue, a sepsis group and a persistent inflammation group were established to investigate differences in severity and pathophysiology.Nevertheless, despite these limitations, we believe that the study sheds light on the intricate mechanisms of iron metabolism during systemic infection and provides a foundation for future studies.In conclusion, it was suggested that hypoferremia due to the effect of hepcidin decreases iron in the environment of extracellular pathogens, the increase in LCN2 levels directly inhibits siderophores during the acute phase of infection, and these effects of hepcidin and LCN2 associated with the inflammatory response prevents iron acquisition by the pathogen in each manner.In an era of prevalent drug-resistant bacteria, a detailed understanding of the infection-iron axis in clinical practice is critical and represents a potential advance in the diagnosis and treatment of infectious diseases in the future.

Ethics approval and consent to participate
This study was conducted in compliance with the Declaration of Helsinki and current ethical guidelines.The Ethics Committee of Niigata University (Approval Number: 2015-2301) approved the study, including the waiver of written informed consent due to the use of residual blood samples in the study and the absence of novel invasive procedures for patients.Information about the study's goals and an opt-out option were provided on the official website of Niigata University School of Medicine.

Study participants and design
At the Niigata University Medical and Dental Hospital (827 beds, tertiary urban hospital), the study included cases of bloodstream infections.The study period was from March 2015 to December 2016, and patients with new positive blood cultures were reviewed daily.A positive blood culture confirmed the diagnosis of bloodstream infection, and single positive cultures of normal skin flora were excluded.
During each case's clinical course, the day of the first positive blood culture was defined as day 1 of illness (D1).Previous in vivo reports indicated that hepcidin reaches its maximum concentration in about 6 h 21 and C-reactive protein (CRP) in 2-3 days 34 .Based on these findings, this study included the test results of each item at two points, D1 and days 2 to 3 of illness (D3), as the acute phase of infection.Additionally, the first day of blood testing after day 10 of illness was defined as D10 and treated as an indicator in the recovery phase.For the purpose of this study, the baseline values of each parameter were defined based on the measurements taken at D10. Eligible patients were adults aged ≥ 18 years who had a blood test at the appropriate time and had residual blood samples available.Treating physicians obtained the laboratory results used in this study during their practice.For missing data and additional testing, the residual plasma samples of D1, D3, and D10 stored at − 80°C were used; no additional blood samples were collected for this study.Finally, 150 samples and 50 cases were obtained, but 6 samples and 2 cases were excluded because there were not enough samples for additional testing.

Figure 1 .
Figure 1.Changes over time in markers of iron metabolism and inflammation in bloodstream infections.Changes over time in inflammatory and iron parameters in patients with bloodstream infections; WBC (a), IL-6 (b), CRP (c), Iron (d), HEP (e) and LCN2 (f) levels were measured at each time point and are shown in boxand-whisker plots.The thick line represents the median, and the boxes represent the interquartile range.The median of each point is connected by a solid line.Logarithmic scale is used for the IL-6 Y-axis.Measurements were compared between points, and P-values were calculated using the Wilcoxon signed-rank test.Statistically significant items are marked with an asterisk (*).WBC white blood cell count, IL-6 interleukin-6, CRP C-reactive protein, HEP hepcidin, LCN2 lipocalin-2.

Figure 2 .
Figure 2.Comparison of laboratory data with or without sepsis.All the participants were divided into two groups: sepsis (n = 36) and non-sepsis(12) groups.WBC (a), IL-6 (b), CRP (c), iron (d), HEP (e), and LCN2 (f) blood levels at D1 were measured and compared between two groups.In box-and-whisker plots, the thick line represents the median, and the boxes represent the interquartile range.The median of each point is connected by a solid line.A logarithmic scale is used for the IL-6 Y-axis.Measurements were compared between points, and P-values were calculated using the Wilcoxon signed-rank test.Statistically significant items are marked with an asterisk (*).WBC white blood cell count, IL-6 interleukin-6, CRP C-reactive protein, HEP hepcidin, LCN2 lipocalin-2. https://doi.org/10.1038/s41598-023-46383-7

Figure 4 .
Figure 4. Principal component analysis for all measured items.Principal component analysis identified the first two principal components, which explained 41.6% of the variation in the dataset.(A) Score plot showing each principal component's score for each sample.Circles, filled circles, and triangles indicate D1, D3 and D10, respectively.(B) Loading plot showing the items loading on each principal component.Items clustered close together on the graph indicate that they vary in the same manner.WBC white blood cell count, NEU neutrophil count, Hb hemoglobin, PLT platelet count, ALB albumin, CRE creatinine, TBIL total bilirubin, IL-6 interleukin-6, CRP C-reactive protein, P-SEP presepsin, TIBC total iron-binding capacity, UIBC unsaturated iron-binding capacity, TSAT transferrin saturation, FER ferritin, HEP hepcidin, LCN2 lipocalin-2.

Table 1 .
Characteristics of participants.Data are expressed as median (IQR) or n (%).SOFA score Sequential Organ Failure Assessment score.*Value at D1.